gmjmcmc: Main algorithm for GMJMCMC TODO: More documentation - borrow...

In jonlachmann/GMJMCMC: Genetically Modified Mode Jumping MCMC

Main algorithm for GMJMCMC TODO: More documentation - borrow from https://github.com/aliaksah/EMJMCMC2016/blob/master/man/EMJMCMC.Rd if applicable.

Description

Main algorithm for GMJMCMC TODO: More documentation - borrow from https://github.com/aliaksah/EMJMCMC2016/blob/master/man/EMJMCMC.Rd if applicable.

Usage

gmjmcmc(
  data,
  loglik.pi = gaussian.loglik,
  loglik.alpha = gaussian.loglik.alpha,
  transforms,
  P = 10,
  N.init = 100,
  N.final = 100,
  probs = NULL,
  params = NULL,
  sub = FALSE
)

Arguments

data	A matrix containing the data to use in the algorithm, first column should be the dependent variable, second should be the intercept and the rest of the columns should be the independent variables.
loglik.pi	The (log) density to explore
loglik.alpha	The likelihood function to use for alpha calculation
transforms	A Character vector including the names of the non-linear functions to be used by the modification and the projection operator.
P	The number of generations for GMJMCMC. The default value is $P = 10$. A larger value like $P = 50$ might be more realistic for more complicated examples where one expects a lot of non-linear structures.
N.init	The number of iterations per population (total iterations = (T-1)*N.init+N.final)
N.final	The number of iterations for the final population (total iterations = (T-1)*N.init+N.final)
probs	A list of the various probability vectors to use
params	A list of the various parameters for all the parts of the algorithm
sub	An indicator that if the likelihood is inexact and should be improved each model visit (EXPERIMENTAL!)

jonlachmann/GMJMCMC documentation built on April 22, 2024, 4:21 a.m.